Fixes.

python/pyarrow/pandas_compat.py

@@ -23,12 +23,11 @@ import re
 import pandas.core.internals as _int
 import numpy as np
 import pandas as pd
-import pickle
 
 import six
 
 import pyarrow as pa
-from pyarrow.compat import PY2, zip_longest  # noqa
+from pyarrow.compat import builtin_pickle, PY2, zip_longest  # noqa
 
 
 def infer_dtype(column):
@@ -433,7 +432,7 @@ def dataframe_to_serialized_dict(frame):
         # If we are dealing with an object array, pickle it instead.
         if isinstance(block, _int.ObjectBlock):
             block_data['object'] = None
-            block_data['block'] = pickle.dumps(values)
+            block_data['block'] = builtin_pickle.dumps(values)
 
         blocks.append(block_data)
 
@@ -470,8 +469,8 @@ def _reconstruct_block(item):
                                 klass=_int.DatetimeTZBlock,
                                 dtype=dtype)
     elif 'object' in item:
-        block = _int.make_block(pickle.loads(block_arr), placement=placement,
-                                klass=_int.ObjectBlock)
+        block = _int.make_block(builtin_pickle.loads(block_arr),
+                                placement=placement, klass=_int.ObjectBlock)
     else:
         block = _int.make_block(block_arr, placement=placement)
 

python/pyarrow/serialization.py

@@ -22,7 +22,8 @@ import sys
 import numpy as np
 
 from pyarrow.compat import builtin_pickle
-from pyarrow.lib import SerializationContext, _default_serialization_context
+from pyarrow.lib import (SerializationContext, _default_serialization_context,
+                         frombuffer)
 
 try:
     import cloudpickle
@@ -43,6 +44,19 @@ def _deserialize_numpy_array_list(data):
     return np.array(data[0], dtype=np.dtype(data[1]))
 
 
+def _pickle_to_buffer(x):
+    pickled = builtin_pickle.dumps(x, protocol=builtin_pickle.HIGHEST_PROTOCOL)
+    return frombuffer(pickled)
+
+
+def _load_pickle_from_buffer(data):
+    as_memoryview = memoryview(data)
+    if six.PY2:
+        return builtin_pickle.loads(as_memoryview.tobytes())
+    else:
+        return builtin_pickle.loads(as_memoryview)
+
+
 # ----------------------------------------------------------------------
 # pandas-specific serialization matters